Statistical Function Tagging and Grammatical Relations of Myanmar Sentences
This work addresses the problem of natural language processing for Myanmar, which has free-phrase-order and complex morphology, but it is incremental as it applies existing methods like CFG and Naive Bayesian to this domain.
The paper tackled the challenge of grammatical relation analysis for Myanmar sentences by developing a context-free grammar (CFG) based system combined with statistical function tagging, achieving good results on both simple and complex sentences.
This paper describes a context free grammar (CFG) based grammatical relations for Myanmar sentences which combine corpus-based function tagging system. Part of the challenge of statistical function tagging for Myanmar sentences comes from the fact that Myanmar has free-phrase-order and a complex morphological system. Function tagging is a pre-processing step to show grammatical relations of Myanmar sentences. In the task of function tagging, which tags the function of Myanmar sentences with correct segmentation, POS (part-of-speech) tagging and chunking information, we use Naive Bayesian theory to disambiguate the possible function tags of a word. We apply context free grammar (CFG) to find out the grammatical relations of the function tags. We also create a functional annotated tagged corpus for Myanmar and propose the grammar rules for Myanmar sentences. Experiments show that our analysis achieves a good result with simple sentences and complex sentences.